In recent years, digital image technologies advance rapidly, and various digital image capturing devices (such as CCD and CMOS) of electronic imaging devices (such as digital cameras, digital camcorders, notebook computers, mobile phones and webcams, etc) are introduced to the market. Not only the imaging quality becomes increasingly higher, but the size of the products also becomes increasingly smaller. As the price is getting lower and lower, these digital imaging devices become more popular. Although many digital imaging devices have come with advanced auto focus and auto exposure functions, yet the electronic imaging devices still determine whether or not to capture an image based on information obtained from the detection of a whole scene. A human face only occupies a small portion of the whole scene, and thus it is difficult for a novice photographer to capture a satisfactory portrait (including a head and an upper body) without having the capability and experience of adjusting shutter and diaphragm correctly.
To provide a smart image capturing function for electronic imaging devices and a high-quality portrait photography for consumers, some manufacturers apply a face detection technique to modern electronic image capturing devices, and different face detection algorithms are disclosed in publications, and the most popular one of the face detection algorithms relates to a face detector designed with the Gentle Adaboost (GAB) algorithm, and the face detector uses Haar-like features for identifying a face and bases on a specific quantity of face image samples to train a face classifier to determine whether or not an image in a digital image is a face, adjusting the focal length of the face in the digital image, automatically adjusting a shutter and a diaphragm according to the focal length, and automatically adjusting the shutter and the diaphragm to obtain a digital image with a clear face. Since a low-end electronic image capturing device available in the market generally comes with the auto focus function for automatically adjusting the shutter and diaphragm, therefore users cannot adjust the shutter and diaphragm manually to set a required depth of field for the foreground and background of the digital image and obtain a digital image with a clear foreground (such as a portrait) and a blurred background in order to avoid the unimportant background from spoiling or interfering the foreground, and show the features and importance of the foreground prominently. Although a high-end electronic image capturing device available in the market generally comes with a mechanism for adjusting the shutter and diaphragm manually, users require a certain level of photography knowledge, capability and experience for adjusting the shutter and diaphragm manually to set the depth of field for the foreground and background of the digital image. Obviously, a general user lack of such capability and experience is unable to produce a digital image with clear foreground and background by the high-end electronic image capturing device.
Therefore, it is an important subject for related electronic image capturing device designers and manufacturers to develop an electronic image capturing device with a smart image capturing function to achieve the effects of meeting the basic image capturing requirements of the general users, compensating their insufficient photography skills, effectively saving the long time of making adjustments, and producing a digital image with clear foreground (such as a portrait) and background.